diff --git a/DESCRIPTION b/DESCRIPTION index b96121b1..4d6be983 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: mlr3tuning Title: Hyperparameter Optimization for 'mlr3' -Version: 0.19.0.9000 +Version: 0.19.1 Authors@R: c( person("Marc", "Becker", , "marcbecker@posteo.de", role = c("cre", "aut"), comment = c(ORCID = "0000-0002-8115-0400")), @@ -25,15 +25,15 @@ License: LGPL-3 URL: https://mlr3tuning.mlr-org.com, https://github.com/mlr-org/mlr3tuning BugReports: https://github.com/mlr-org/mlr3tuning/issues Depends: - mlr3 (>= 0.14.1), + mlr3 (>= 0.17.0), paradox (>= 0.10.0), R (>= 3.1.0) Imports: - bbotk (>= 0.7.2), + bbotk (>= 0.7.3), checkmate (>= 2.0.0), data.table, lgr, - mlr3misc (>= 0.11.0), + mlr3misc (>= 0.13.0), R6 Suggests: adagio, @@ -47,8 +47,6 @@ Suggests: rpart, testthat (>= 3.0.0), xgboost -Remotes: - mlr-org/mlr3 Config/testthat/edition: 3 Config/testthat/parallel: true Encoding: UTF-8 diff --git a/NEWS.md b/NEWS.md index a2f40a00..ca9f0e10 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,5 +1,6 @@ -# mlr3tuning (development version) +# mlr3tuning 0.19.1 +* refactor: Speed up the tuning process by minimizing the number of deep clones and parameter checks. * fix: Set `store_benchmark_result = TRUE` if `store_models = TRUE` when creating a tuning instance. * fix: Passing a terminator in `tune_nested()` did not work. diff --git a/R/zzz.R b/R/zzz.R index 7695f430..6df77a57 100644 --- a/R/zzz.R +++ b/R/zzz.R @@ -8,6 +8,9 @@ "_PACKAGE" .onLoad = function(libname, pkgname) { + # CRAN OMP THREAD LIMIT + Sys.setenv("OMP_THREAD_LIMIT" = 2) + # nocov start x = utils::getFromNamespace("mlr_reflections", ns = "mlr3") x$tuner_properties = "dependencies" diff --git a/README.md b/README.md index 9c61d5c5..adb4eddf 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ # mlr3tuning -Package website: [release](https://mlr3tuning.mlr-org.com/) | +Package website: [release](https://mlr3tuning.mlr-org.com/) \| [dev](https://mlr3tuning.mlr-org.com/dev/) @@ -34,12 +34,12 @@ The package is built on the optimization framework mlr3tuning is extended by the following packages. - - [mlr3tuningspaces](https://github.com/mlr-org/mlr3tuningspaces) is a +- [mlr3tuningspaces](https://github.com/mlr-org/mlr3tuningspaces) is a collection of search spaces from scientific articles for commonly used learners. - - [mlr3hyperband](https://github.com/mlr-org/mlr3hyperband) adds the +- [mlr3hyperband](https://github.com/mlr-org/mlr3hyperband) adds the Hyperband and Successive Halving algorithm. - - [mlr3mbo](https://github.com/mlr-org/mlr3mbo) adds Bayesian +- [mlr3mbo](https://github.com/mlr-org/mlr3mbo) adds Bayesian Optimization methods. ## Resources @@ -47,36 +47,36 @@ mlr3tuning is extended by the following packages. There are several sections about hyperparameter optimization in the [mlr3book](https://mlr3book.mlr-org.com). - - Getting started with [hyperparameter +- Getting started with [hyperparameter optimization](https://mlr3book.mlr-org.com/chapters/chapter4/hyperparameter_optimization.html). - - [Tune](https://mlr3book.mlr-org.com/chapters/chapter4/hyperparameter_optimization.html#sec-model-tuning) +- [Tune](https://mlr3book.mlr-org.com/chapters/chapter4/hyperparameter_optimization.html#sec-model-tuning) a support vector machine on the Sonar data set. - - Learn about [tuning +- Learn about [tuning spaces](https://mlr3book.mlr-org.com/chapters/chapter4/hyperparameter_optimization.html#sec-defining-search-spaces). - - Estimate the model performance with [nested +- Estimate the model performance with [nested resampling](https://mlr3book.mlr-org.com/chapters/chapter4/hyperparameter_optimization.html#sec-nested-resampling). - - Learn about [multi-objective +- Learn about [multi-objective optimization](https://mlr3book.mlr-org.com/chapters/chapter5/advanced_tuning_methods_and_black_box_optimization.html#sec-multi-metrics-tuning). The [gallery](https://mlr-org.com/gallery-all-optimization.html) features a collection of case studies and demos about optimization. - - Learn more advanced methods with the [Practical Tuning +- Learn more advanced methods with the [Practical Tuning Series](https://mlr-org.com/gallery/series/2021-03-09-practical-tuning-series-tune-a-support-vector-machine/). - - Optimize an rpart classification tree with only a [few lines of +- Optimize an rpart classification tree with only a [few lines of code](https://mlr-org.com/gallery/optimization/2022-11-10-hyperparameter-optimization-on-the-palmer-penguins/). - - Simultaneously optimize hyperparameters and use [early +- Simultaneously optimize hyperparameters and use [early stopping](https://mlr-org.com/gallery/optimization/2022-11-04-early-stopping-with-xgboost/) with XGBoost. - - Make us of proven [search +- Make us of proven [search space](https://mlr-org.com/gallery/optimization/2021-07-06-introduction-to-mlr3tuningspaces/). - - Learn about +- Learn about [hotstarting](https://mlr-org.com/gallery/optimization/2023-01-16-hotstart/) models. - - Run the [default hyperparameter +- Run the [default hyperparameter configuration](https://mlr-org.com/gallery/optimization/2023-01-31-default-configuration/) of learners as a baseline. - - Use the +- Use the [Hyperband](https://mlr-org.com/gallery/series/2023-01-15-hyperband-xgboost/) optimizer with different budget parameters. diff --git a/inst/WORDLIST b/inst/WORDLIST index 09641d44..348d15c1 100644 --- a/inst/WORDLIST +++ b/inst/WORDLIST @@ -52,16 +52,17 @@ hotstart hotstarting hyperband irace +iteratively mbo mlr nloptr +optimizers parallelization parallelize param parametrized rpart subclasses -svm th trafo tuningspaces diff --git a/tests/testthat/test_mlr_callbacks.R b/tests/testthat/test_mlr_callbacks.R index b44f930d..060571d3 100644 --- a/tests/testthat/test_mlr_callbacks.R +++ b/tests/testthat/test_mlr_callbacks.R @@ -1,4 +1,5 @@ test_that("early stopping callback works", { + skip_on_cran() skip_if_not_installed("mlr3learners") skip_if_not_installed("xgboost") library(mlr3learners) # nolint